Method and device for provisioning collective perception in communication networks

ABSTRACT

A method and device for provisioning collective perception in a communication network is disclosed. The method includes receiving a perception data from a plurality of communication entities in the communication network upon satisfaction of at least one of predefined criteria. The method further includes assimilating the perception data in a global collective experience record table, based on at least one perception data category associated with the predefined criteria. The method includes processing the perception data associated with each of the at least one perception data category to create composite perception information based on entries in the global collective experience record table. The method further includes determining perception distribution information to be shared with at least one communication entity from the plurality of communication entities, based on the composite perception information. The method includes transmitting the perception distribution information to the at least one communication entity, in response to determining.

TECHNICAL FIELD

This disclosure relates generally to communication networks and moreparticularly to method and device for provisioning collective perceptionin communication networks.

BACKGROUND

In case of Internet of Things (IoT) communications, the privacy andsecurity needs change dynamically depending on the context or purpose,during an engagement (session) as well as across engagements. One of theconventional systems proposes a mechanism of dynamic, adaptive andcomposite privacy and security mechanism for IoT communication. Itproposes to form and dynamically adapt the perception pre-engagement andengagement phase based on global and local perception inputs. Thecommunication filters during pre-engagement and engagement phase arethen adapted dynamically based on the updated perception. It howeverfails to describe how the global perception, which is a collection ofperception inputs across multiple IoT sessions involving multiple IoTnetworks is assimilated. Further, this conventional system does notdescribe how the global perception inputs are distributed other thanmentioning that it will done upon request from InterConnect Gateway(ICG) or upon receiving a notification of a security/privacy relatedexception.

Another conventional system presents an IoT security architecture whichaddresses security needs at different places in an IoT network as wellas across the various protocol layers and functions. It proposes aTrusted Network Module (TSM) which handles security incident management,risk management and security strategy configuration management. The TSMis mainly responsible for the accreditation of network users, thecollection and distribution of security management information such asusers' authorization, and the audit and control of related securityissues. However, this conventional system fails to address how securityincidents enable refinement of security settings for future IoTcommunication involving the same users/devices in the same context or ina different context, as well as similar communication involving adifferent set of users/devices. Further, this conventional system onlyaddresses security aspects, and not privacy or other aspects of IoTcommunication.

Yet another conventional system discusses about the current status,challenges and prospective measures of IoT security. It proposes a trustestablishment mechanism, such that, access control is provided based onthe device and the current owner by an entitlement system. As owners ofthe device change, the access control levels also change. Thisconventional system also proposes access-control delegation. However,this conventional system fails to address the dynamic change in needs ofaccess for a particular device depending on the context and the purposeof communication, the communicating entities and correspondinglyaddressing this need by taking also into consideration past transactionsinvolving the communicating entities. Additionally, this conventionalsystem only addresses security aspects, and not privacy or other aspectsof IoT communication.

Another conventional system proposes a policy-based privacy mechanism inwhich the privacy policy generator automatically picks up policies orprivacy settings that are pre-specified by the user in a social networkor collaboration tool, and creates a compatible privacy policy. Thegenerator includes tools to resolve conflicting settings and is able togeneralize data types. It also allows the user to manually fine-tune theprivacy policy. However, this mechanism does not focus on the securityaspects, and also does not address the dynamic changes in privacy andsecurity requirements during the course of an IoT interaction.

Yet another conventional system proposes a context-aware and trust-basedsecurity and privacy framework in which security policies areimplemented as ECA rules. However, the proposed framework does notdynamically adapt to changes in context, trust-level, environment, etc.during the interaction. The framework will also encounter limitationswhen faced with new/unknown service-oriented and inter-IoT interactionscenarios without any human intervention.

The above discussed conventional systems have one or more of thefollowing limitations: Failure to provide effective security/privacy forfunctional (purpose and context driven) communication, failure toprovide dynamic and need-based device agnostic privacy and security incommunication beyond access control, failure to provide mechanism ofcollective-experience-based-communication (assimilating past experiencesacross IoT networks and communications sharing the collective relevantexperience with relevant IoT devices and networks, and enabling itsappropriate use for future IoT communication) based on the nature(context and purpose) and communicating entities.

SUMMARY

In one embodiment, a method for provisioning collective perception in acommunication network is disclosed. The method includes receiving, by anetwork device, a perception data from a plurality of communicationentities in the communication network upon satisfaction of at least oneof predefined criteria. The method further includes assimilating, by thenetwork device, the perception data in a global collective experiencerecord table in response to receiving the perception data from theplurality of communication entities, based on at least one perceptiondata category associated with the predefined criteria. The methodincludes processing, by the network device, the perception dataassociated with each of the at least one perception data category tocreate composite perception information for each of the at least oneperception data category based on entries in the global collectiveexperience record table, wherein the perception data is processed basedon the associated perception data category. The method further includesdetermining, by the network device, perception distribution informationto be shared with at least one communication entity from the pluralityof communication entities, based on the composite perception informationcreated for each of the at least one perception data category. Themethod includes transmitting, by the network device, the perceptiondistribution information to the at least one communication entity, inresponse to determining.

In another embodiment, a network device for provisioning collectiveperception in a communication network is disclosed. The network deviceincludes a processor and a memory storing processor instructions that,when executed by the processor, cause the processor to receive aperception data from a plurality of communication entities in thecommunication network upon satisfaction of at least one of predefinedcriteria. The processor instructions further cause the processor toassimilate the perception data in a global collective experience recordtable in response to receiving the perception data from the plurality ofcommunication entities, based on at least one perception data categoryassociated with the predefined criteria. The processor instructionsfurther cause the processor to process the perception data associatedwith each of the at least one perception data category to createcomposite perception information for each of the at least one perceptiondata category based on entries in the global collective experiencerecord table, wherein the perception data is processed based on theassociated perception data category. The processor instructions furthercause the processor to determine perception distribution information tobe shared with at least one communication entity from the plurality ofcommunication entities, based on the composite perception informationcreated for each of the at least one perception data category. Theprocessor instructions further cause the processor to transmit theperception distribution information to the at least one communicationentity, in response to determining.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this disclosure, illustrate exemplary embodiments and, togetherwith the description, serve to explain the disclosed principles.

FIG. 1 illustrates an environment (that is exemplary) in which variousembodiments may function.

FIGS. 2A and 2B illustrate network level view of a system forprovisioning collective perception in a communication network andinteraction between various components of a perception management modulewithin the system, in accordance with an embodiment.

FIG. 3 illustrates a flow chart of a method for provisioning collectiveperception in a communication network, in accordance with an embodiment.

FIG. 4 illustrates a flow chart of a method for provisioning collectiveperception in a communication network, in accordance with anotherembodiment.

FIG. 5 illustrates a flowchart of a method for assimilating theperception data in a global collective experience table in response toreceiving the perception data from a plurality of communicationentities, in accordance with an embodiment.

FIG. 6 illustrates a flowchart of a method for processing perceptiondata associated with one or more perception data categories to createcomposite perception information is illustrated, in accordance with anembodiment.

DETAILED DESCRIPTION

Exemplary embodiments are described with reference to the accompanyingdrawings. Wherever convenient, the same reference numbers are usedthroughout the drawings to refer to the same or like parts. Whileexamples and features of disclosed principles are described herein,modifications, adaptations, and other implementations are possiblewithout departing from the spirit and scope of the disclosedembodiments. It is intended that the following detailed description beconsidered as exemplary only, with the true scope and spirit beingindicated by the following claims.

Additional illustrative embodiments are listed below. In one embodiment,an environment 100 (that is exemplary) in which various embodiments mayfunction is illustrated in FIG. 1. Environment 100 includes a pluralityof IoT device networks, such that each IoT device network is associatedwith an IoT subscriber. The plurality of IoT device networks may includea car IoT network 102 that is associated with owner of the car (in otherwords, an IoT subscriber) that may be moving from one point to another.Car IoT network 102 includes a plurality of car IoT devices. Theplurality of IoT networks may also include a home IoT network 104associated with one or more owners of the house. Home IoT network 104also includes a plurality of home IoT devices.

At first time instant, car IoT network 102 is located at a location 106that may be closer to home. For example, the car may be parked in agarage at the home. As a result, both car IoT network 102 and home IoTnetwork 104 communicate with a gateway 108, which enables communicationbetween car IoT network 102 and home IoT network 104. Gateway 108 may bean IoT gateway or may be a smartphone. Alternatively, IoT device in eachof car IoT network 102 and home IoT network 104 may directly communicatewith a Macro cellular and Core Network (MCN) 110 without requiringgateway 108.

Subsequently, the car may move from location 106, which is closer tohome, to a location 112 that may be a gas station, Location 112 alsoincludes a gas station IoT network 114. Once the car is at location 112,car IoT network 102 communicates with MCN 110 and gas station IoTnetwork 114 through a gateway 116. Gas station IoT 114 also communicateswith MCN 110 through gateway 116, MCN 110 further is in communicationwith a plurality of IoT applications, for example, an IoT application118 and an IoT application 120.

The connectivity of different IoT networks facilitated through gatewaysand MCN 110 enables immediate resolution of any issue that is detectedby one or more IoT device in any one of these IoT networks, for example,car IoT network 102. For example, the car may have one or more issuesthat may or may not be critical and need to be fixed either immediatelyor at a service station at a certain distance from the car. The issuesdetected by car IoT network 102 may include, but are not limited toimpending collision with another vehicle, heated up engine, almost emptypetrol tank, low air pressure in a tyre, non-critical service request,and reminder for periodic car maintenance service. In a similar manner,issues detected by home IoT network 104 may include renewal ofsubscription for a channel in the in-house entertainment system, a gasleak, a fire alarm going off, and leakage of water. It will be apparentto a person skilled in the art that the invention may be implemented inany communication network and is not limited to environment 100.

Referring now to FIGS. 2A and 2B, network level view of a system 200 forprovisioning collective perception in a communication network andinteraction between various components of a Perception Management Module(PMM) 202 within system 100 is illustrated, in accordance with anembodiment. In system 200, PMM 202 is communicatively coupled to aplurality of Inter-Connect Gateways (ICG), for example, an ICG 204 andan ICG 206. Each of the plurality of ICGs are further communicativelycoupled to a plurality of gateways. For example, ICG 204 may becommunicatively coupled to gateways 208 and 210, while ICG 206 may becommunicatively coupled to gateways 212 and 214. Details of theplurality of ICG and the plurality of gateways is explained in detail ina co-pending application, titled, “METHOD AND SYSTEM FOR DYNAMICALLYADAPTING PRIVACY AND SECURITY FOR INTERNET OF THINGS (IOT)COMMUNICATION,” having application number, “US20170272940A1,” and filedon, “Mar. 16, 2017.”

PMM 202 may be part of a network device (not shown in FIG. 2b ). Thenetwork device, for example, may include, but is not limited to anapplication server, a server, a gateway, or a router. The network devicemay include a processor and a memory that stores processor instructions,which when executed causes the processor to perform functionalitiesdefined for PMM 202. PMM 202 may further include an experienceassimilation module (EA-MOD) 204, a configuration module (PER-CM-MOD)206, a perception processing module (PER-PROC-MOD) 208, a perceptionscheduler and responder module (PER-SCHED-RSP-MOD) 210, a communicationsmodule (PER-COMM-MOD) 212, a plurality of databases, for example, acollective experience database 214, and a perception store 216.

EA-MOD 204 is responsible for receiving all the perception data from acommunication entity in the communication network, for example, the ICG(or any other IoT network element in case of exceptions) throughPER-COMM-MOD 212. The perception data may include, but are not limitedto: data when one or more exceptions were encountered, data when asession ended, or during partial completion of a communication session(for example, a specific transaction within the session was completed inan IoT session). EA-MOD 204 converts the received perception-data into astandard format based one or more perception data categories, that mayinclude, exception-perception data category and regular-perception datacategory.

The perception data associated with the exception-perception datacategory (EXC-FEED) is created upon receiving perception data from acommunication entity (for example, the IoT network/ICG) when anexception has occurred. In an exemplary embodiment, EXC-FEED may berepresented using table 1 given below. CRE denotes Communicating RemoteEntity.

TABLE 1 SESSION- Field INFO UID ID-CLASS ID-DET EXC-CTX Description ofSession ID and CRE-ID Nature of Identity details Exception contentsclass CRE (CRE such as group id Context class) or individual id

In the above table, exception context may include details, such as, typeof exception (for example, security-exception (SEC-EXC),privacy-exception (PRIV-EXC), or communication exception (COMM-EXC)),details of the exception (for example, unencrypted transmission, privacyexposure, or jamming), environment/context of the exception, whichincludes details such as location category (public/private), location(GPS co-ordinates or location type such as gas station, etc.), time ofday, details of when the exception occurred, for example, whenexchanging sensitive information, during session setup/extension, changein purpose, arrival of a new party, etc.

The perception data associated with the regular-perception data category(PER-FEED) is created upon receiving perception data from acommunication entity, when a communication session has ended, or duringpartial completion of a communication session. In an exemplaryembodiment, PER-FEED may be represented using table 2 given below:

TABLE 2 EXP- EXP- SEC- PRIV- EXP-NEED- SESSION- ID- LVL- LVL- FULFILL-Field INFO UID CLASS ID-DET CRE CRE REC-CRE Description Session CRE-Nature Identity Usual Usual Aggregated of ID ID of details such SecurityPrivacy Fulfilment contents and CRE as group id or level of level ofRecord of class (class) individual id the CRE the CRE CRE

Based on the above perception inputs, EA-MOD 204 creates a GlobalCollective Experience Record (GCE-REC) entry in the Global CollectiveExperience Record Table (GCE-REC-TABLE) if an entry does not exist forthat CRE for that specific communication session (for example, IoTsession), else it updates the relevant entry in the GCE-REC-TABLE. Thecontents of each entry in the GCE-REC-TABLE is shown below. One GCE-RECentry is created in the GCE-REC-TABLE for every communication session(for example IoT session) for each CRE. In an exemplary embodiment, theGCE-REC may be depicted by table 3 and the GCE-REC-TABLE is depicted bytable 4 given below:

TABLE 3 EXP- EXP- EXP- NEED- SEC- PRIV- FULFILL- SESSION- ID- LVL- LVL-REC- Field INFO UID CLASS ID-DET CRE CRE CRE EXC-INFO DescriptionSession CRE- Nature Identity Usual Usual Aggregated Details of ID ID ofCRE details Security Privacy Fulfilment exceptions and (class) such aslevel level of Record encountered class group id or of the the of CREindividual CRE CRE id

Exception contexts may include all exception contexts received up tothat point of time for the session (i.e., accumulation of all relevantinfo from EXC-FEEDS received for the session).

TABLE 4 EXP- EXP- EXP- NEED- SEC- PRIV- FULFILL- SESSION- ID- LVL- LVL-REC- INFO UID CLASS ID-DET CRE CRE CRE EXC-INFO Session CRE- Class1Group-id3 Sec- Priv- 70% 1. High interference (2 ID1 ID1 (car (Car loTId) Level-3 Level-4 instances), details loT) (secure (2-level such aschannel authentication, <communication only) masking channel used, timeof stamp, info individual exchanged, etc.> id) 2. Use of unencryptedchannel - 1 instance, details such as <info exchanged, reason forexception - e.g., low battery, etc.> Session CRE- ID2 ID1 . . . SessionCRE- ID k ID2 . . . Session CRE- ID m ID n . . .

EA-MOD 204 passes the relevant inputs to PER-CM-MOD 206 along with theinfo on which entries in the GCE-REC-TABLE were created or updated. TheGCE-REC-TABLE is persisted in collective experience database 214.

PER-CM-MOD 206 obtains input configurations from the network operator,and passes them to the relevant modules within PMM 202. Examples of suchconfiguration parameters or inputs and their use include initialthreshold settings for specific (or generic) minor exceptions forsending updated perception data to the communication entities (forexample ICGs) associated with PMM 202 (and consequently to the involvedIoT networks). The configuration parameters further includecommunication channel configurations (for example, security, latency,reliability) for obtaining the perception data, and for communicatingthe perception information, initial settings and thresholds associatedwith parameters such as service-fulfillment-need of communicating party(consumer), service-fulfilment-ability of communicating party(provider), delivered-service-quality, reliability, authenticity, etc.

The configuration parameters further include EXC-CRT-MAPPING-TABLE,which provides the criticality level of the exception based on exceptiontype and exception details; EXC-THRES, which are thresholds for numberof exceptions within a session and includes thresholds for specificexceptions as well as exception type. In addition, thresholds for numberof exceptions within a time window (e.g., 1 minute) may also beincluded; REC-PRIV-LVL-TABLE, which contains the mapping of recommendedprivacy level based on the privacy exceptions encountered during thesession, and comparing with past trends; REC-SEC-LVL-TABLE, whichcontains the mapping of recommended security level based on securityexceptions encountered during the session, and comparing with pasttrends; REC-PRIV-COMPL-LVL-TABLE, which contains the mapping of privacycompliance level based on the number and type of privacy exceptionsencountered during the session; REC-SEC-COMPL-LVL-TABLE, which containsthe mapping of security compliance level based on the number and type ofsecurity exceptions encountered during the session;REC-NEED-FULFILL-LVL-TABLE, which contains the mapping of needfulfillment level based on the exception type;NEED-FULFILL-FACTOR-TABLE, which contains the mapping ofNEED-FULFILL-FACTOR based on the number of exceptions; NEED-SCF, whichis a factor that indicates the influence of past need fulfillment recordon the recommended need fulfillment level (value is between 0 and 1);REL-VAUE-TABLE, which contains the mapping of REL-VALUE based on theexception type and criticality level of the exception; REL-FACTOR-TABLE,which contains the REL-FACTOR mapping based on the number of exceptionsthat have occurred thus far in the session; and REL-SCF, which is afactor that indicates the influence of reliability record on therecommended reliability level (value is between 0 and 1).

PER-PROC-MOD 208 is responsible for processing the perception data andforming the composite perception information. PER-PROC-MOD 208 processesthe perception data on a periodic basis (for example, once every 15minutes) or upon specific trigger by EA-MOD 204. Upon receipt ofPER-FEED from EA-MOD 204, PER-PROC-MOD 208 processes the PER-FEED andcreates or updates the Global Collective Perception Record(GLOB-COL-PER-REC) for the CRE in the GLOB-COL-PER-REC-TABLE. In anexemplary embodiment, the layout of the GLOB-COL-PER-REC may berepresented by table 5 and the GLOB-COL-PER-TABLE by table 6 below:

TABLE 5 USU- USU- AGGREG- AGGREG- AGGREG- AGGREG- SEC- PRIV- NEED- SEC-PRIV- REL- Field ID- LVL- LVL- FULFILL- COMPL- COMPL- REC- name UIDCLASS ID-DET CRE CRE REC-CRE REC-CRE REC-CRE CRE PERC_SCORE DescriptionCRE-ID Nature Identity Usual Usual Aggregated Aggregated AggregatedAggregated Overall of CRE details such Security Privacy FulfilmentSecurity Privacy Reliability Perception (class) as group id level oflevel Record of Compliance Compliance Rec Score or individual the of theCRE Record Record of id CRE CRE of CRE CRE

TABLE 6 USU- USU- AGGREG- AGGREG- AGGREG- AGGREG- SEC- PRIV- NEED- SEC-PRIV- REL- ID- LVL- LVL- FULFILL- COMPL- COMPL- REC- UID CLASS ID-DETCRE CRE REC-CRE REC-CRE REC-CRE CRE PERC_SCORE CRE- Class1 Group-id3Sec- Priv- 60% 75% 72% 65% 68% ID1 (car (Car loT Id) Level-3 Level-4loT) (secure (2-level channel authentication, only) masking ofindividual id) CRE- . . . . . . . . . . . . . . . . . . . . . . . . . .. ID2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . CRE- .. . . . . . . . . . . . . . . . . . . . . . . . . . IDn

AGGREG-REL-REG-CRE is an aggregated score that is computed taking intoconsideration privacy compliance, security compliance, need fulfillmentlevel, and all exceptions. It may be computed as a weighted average ofthese attributes. The PERC-SCORE (overall perception score) is anindicative score of the perception of the CRE, for example, to give anindication of whether the CRE is reliable and trustworthy, complies toprivacy and security, fulfills the needs, etc. It may be an index valueon a fixed scale, for example, 1-5, with 1 being lowest (so it is notrecommended to establish a session with the CRE, or if a session isbeing established, act with utmost caution and/or have lowest level ofexpectations with respect to fulfillment of need), and 5 being thehighest (it is highly recommended to establish a session with the CRE).

Upon receipt of the EXC-FEED from EA-MOD 204, PER-PROC-MOD 208 processesit and creates or updates the Global Selective Perception Record(GLOB-SEL-PER-REC) for the CRE in the Global Selective Perception RecordTable (GLOB-SEL-PER-REC-TABLE). In an exemplary embodiment, the layoutof the GLOB-SEL-PER-REC is depicted in table 7 and theGLOB-SEL-PER-REC-TABLE is depicted in table 8 given below:

TABLE 7 REC- REC- REC- NEED- EXC- SEC- PRIV- FULFILL- Field ID- CRT-LVL- LVL- LVL- Name UID CLASS ID-DET LVL CRE CRE CRE Description CRE-Nature Identity EXC Recommended Recommended Recommended ID of detailsCriticality Security Privacy Need CRE such as Level level of levelFulfilment (class) group id the CRE of the Level of or CRE CREindividual id REC- PRIV- REC- REC-SEC- COMPL- REL- Overall Field COMPL-LVL- LVL- REC- Name LVL-CRE CRE CRE CRE Description RecommendedRecommended Recommended Overall Security Privacy ReliabilityRecommendation Compliance Compliance Level for the Level of Level CRECRE of CRE

TABLE 8 REC- REC- NEED- REC- REC- EXC- SEC- FULFILL- REC-SEC- PRIV- REL-Overall ID- CRT- LVL- REC-PRIV- LVL- COMPL- COMPL- LVL- REC- UID CLASSID-DET LVL CRE LVL-CRE CRE LVL-CRE LVL-CRE CRE CRE CRE- Class Group-id3Criticality- Sec- Priv-Level-4 60% 70% 66% 65% 50% ID1 1 (car (Car loTId) Level-3 Level-4 (2-level (Neutral) loT) (high) (secureauthentication, and masking encrypted) of individual id) CRE- ID2 . . .CRE- IDk

Whenever PER-PROC-MOD 208 updates the GLOB-COL-PER-REC-TABLE, it fetchesrelevant entries from the GLOB-SEL-PER-REC-TABLE as one of the inputsapart from the inputs provided by EA-MOD 204 and the GCE-REC-TABLE. Theentries in the GLOB-SEL-PER-REC-TABLE are removed upon taking them intoconsideration for processing while updating the GLOB-COL-PER-REC-TABLE,and when there are no outstanding transmissions by PER-COMM-MOD 212(determined by checking the transmission schedule and transmissionstatus) of those entries.

Whenever PER-PROC-MOD 208 performs any processing of perception inputs,it passes relevant information to PER-SCHED-RSP-MOD 210 to enableappropriate scheduling of the transmission of perception information.PER-PROC-MOD 208 also adapts the entries in the REC-PRIV-LVL-TABLE, theREC-SEC-LVL-TABLE, the REC-PRIV-COMPL-LVL-TABLE, theREC-SEC-COMPL-LVL-TABLE, and the REC-NEED-FULFILL-LVL-TABLE based on thelearning from past sessions. The learning may be performed by comparingpresent exception trends with past trends in historical data usingwell-known analytics or machine learning techniques, or using anyproprietary algorithms also. Such learning may be performed usingdedicated processors which are appropriate for such complex computationsinvolving a large data set (and may be custom-built or well-known ones).

PER-PROC-MOD 208 includes recent entries of the GCE-REC-TABLE in-memoryfor fast access. PER-PROC-MOD 208 also contains the recently modifiedentries of the GLOB-COL-PER-REC-TABLE and relevant unsent entries of theGLOBAL-SEL-PER-REC-TABLE in-memory for fast access. Persistence of theGLOB-COL-PER-REC-TABLE and the GLOB-SEL-PER-REC-TABLE is taken care bydedicated databases (i.e., collective experience database 214 andperception store 216, respectively).

PER-SCHED-RSP-MOD 210 is responsible for receiving the perceptionrequest (PERC-REQST) from PER-COMM-MOD 212 and passing the request toPER-PROC-MOD 208. Upon receiving the perception data to be sent inresponse to the PERC-REQST, PER-SCHED-RSP-MOD 210 schedules thetransmission of the response (PERC-RSP). The PERC-REQST includesinformation, such as, but not limited to identity of the requestor andthe CRE, relevant information obtained/collected about the sessionand/or the CRE (for example, purpose), context (location, presence ofother parties, etc.), priority/criticality (for example, an IoTcommunication session involving highly critical and low latencycommunication exchange is of higher priority).

PER-SCHED-RSP-MOD 210 is also responsible for scheduling thetransmission of perception data to one or more communication entities(for example, ICGs). Two possible cases exist, first, when transmissionof perception data arises out of one or more exception feeds, due towhich the GLOB-SEL-PER-REC-TABLE has been modified. The transmissionschedule of the perception information to be sent could depend on thecriticality of the exception (for example, highly critical impliesimmediate transmission). Second, when transmission of perception dataarising out of updates to the GLOB-COL-PER-REC-TABLE. In this case, thetransmission schedule could depend on the extent of updates to therelevant GLOB-COL-PER-REC entries. For example, in case of a drasticchange in the PERC-SCORE, the information may be scheduled to betransmitted with a lower latency between successive transmissions.

PER-COMM-MOD 212 is responsible for receiving the exception-perceptiondata and the regular-perception data from one or more communicationentities (for example, the ICG) and passing them to PER-PROC-MOD 208.PER-COMM-MOD 212 is also responsible for receiving the perceptionrequest from a communication entity (for example, the ICG) and passingthem to PER-SCHED-RSP-MOD 210 and for sending the perception data to theICG according to the schedule as provided by PER-SCHED-RSP-MOD 210 andusing the appropriate communication channel based on the priority andsecurity requirements.

With regard to the databases, collective experience database 214includes the GCE-REC-TABLE entries. Collective experience database 214is updated by EA-MOD 204 and accessed by PER-PROC-MOD 208. Collectiveexperience database 214 may involve fast access to enable near real-timeprocessing of the experience records. Perception store 216 includes theGLOB-COL-PER-REC-TABLE and GLOB-SEL-PER-REC-TABLE entries. Perceptionstore 216 is updated by PER-PROC-MOD 208 and accessed byPER-SCHED-RSP-MOD 210.

Referring now to FIG. 3, a flow chart of a method for provisioningcollective perception in a communication network is illustrated, inaccordance with an embodiment. The communication network, for example,may be an IoT network. At step 302, the network device may receiveperception data from a plurality of communication entities in thecommunication network upon satisfaction of one or more predefinedcriteria. In case the communication network is an IoT network, theplurality of communication entities may include one or more of an IoTdevice, an IoT GW, or an ICG.

The one or more predefined criteria may include, but are not limited tooccurrence of an exception during a communication session in thecommunication network, partial completion of the communication session,or completion of the communication session. In an embodiment,PER-COMM-MOD 212 in PMM 202 receives perception data (or perceptioninputs) from an ICG (which may have been generated at the ICG or sentfrom an IoT network, via the ICG). The perception data may have beenreceived by PER-COMM-MOD 212 (from the ICG) upon satisfaction of one ormore of the predefined criteria. PER-COMM-MOD 212 then passes thereceived perception data to EA-MOD 204.

At step 304, based on one or more perception data categories associatedwith the predefined criteria, the network device may assimilate theperception data in a Global Collective Experience Record Table(GCE-REC-TABLE) in response to receiving the perception data from theplurality of communication entities. The one or more perception datacategories may include an exception-perception data category and aregular-perception data category. In order to assimilate the perceptiondata, the network device may ascertain the relevant perception datacategory from the one or more perception data categories for theperception data. In an embodiment, in response to ascertaining, thenetwork device may update the GCE-REC-TABLE. This is further explainedin detail in conjunction with FIG. 5.

In an embodiment, upon receiving the perception data, EA-MOD 204 firstascertains the nature of perception data, i.e., whether it is associatedwith an exception-perception data category or regular-perception datacategory, which is received during or after a session has ended (i.e.,normal session-related perception data). To this end, EA-MOD 204examines contents of the perception data. By way of an example, presenceof exception-related information means that the perception data isassociated with exception-perception data category. Based on thisanalysis, EA-MOD 204 may format the perception data into data associatedwith exception-perception data category or regular-perception datacategory. Thereafter, EA-MOD 204 sends the perception data associatedwith a perception data category along with information regardingupdating of the GCE-REC-TABLE to PER-PROC-MOD 208 for furtherprocessing.

Based on a perception data category associated with the perception data,at step 306, the network device may process the perception data (inputs)associated with each of the one or more perception data categories tocreate a composite perception information for each of the one or moreperception data categories. The perception data may be processed basedon the associated perception data category. The perception dataassociated with each of the one or more perception data categories maybe processed periodically after predefined time period or in response toa predefined trigger event. In other words, relevant entries in a GlobalSelective Perception Record Table (GLOBAL-SEL-PER-REC-TABLE) or in aGlobal Collective Perception Record Table (GLOBAL-COL-PER-REC-TABLE) maybe created or updated for the perception data associated with theexception-perception data category and the regular-perception datacategory.

The composite perception information may include a selective perceptioninformation and a collective perception information. The selectiveperception information may include one or more of, but is not limited toone or more Identifiers (IDs), group ID, class, security level, privacylevel, aggregated fulfillment record, aggregated security compliancerecord, aggregated privacy compliance record, aggregated reliabilityrecord, or overall perception score. Similarly, the collectiveperception information may include one or more of, but is not limited toID, group ID, class, exception criticality level, recommended securitylevel, recommended privacy compliance level, recommended fulfillmentlevel, recommended compliance level, recommended privacy compliancelevel, recommended reliability level, or overall recommendation.

When the network device processes the relevant entries in theGCE-REC-TABLE associated with the exception-perception data category,the network device may update the GLOB-SEL-PER-REC-TABLE that includesthe selective perception information. Similarly, when the network deviceprocesses the relevant entries in the GCE-REC-TABLE associated with theregular-perception data category, the network device may update theGLOB-COL-PER-REC-TABLE that includes the collective perceptioninformation. In an embodiment, PER-PROC-MOD 208 processes the receivedperception data and updates the GLOB-SEL-PER-REC-TABLE and theGLOB-COL-PER-REC-TABLE. This is further explained in detail inconjunction with FIG. 5.

Based on the composite perception information created for the one ormore perception data categories, the network device, at step 308, maydetermine perception distribution information to be shared with one ormore communication entities from the plurality of communicationentities. The perception distribution information may be determinedafter predefined time period or in response to a predefined triggerevent. Thus, there may be two possible scenarios. In the first scenario,the perception distribution information to be shared with the one ormore communication entities may be determined in response to a receivedperception request. This is further explained in conjunction with FIG.4. In the second scenario, the perception distribution information to beshared with the one or more communication entities may be determined inresponse to a predefined trigger event/exception or periodically afterexpiry of a time period.

In an embodiment, in response to the perception request, PER-PROC-MOD208 prepares the perception distribution information for the specificcommunication network (for example, an IoTN) for which the perceptionrequest was received. In order to prepare the perception distributioninformation, for selective perception information, PER-PROC-MOD 208checks if there is any pending record in the GLOB-SEL-PER-REC-TABLE, bychecking pending records with a matching CRE-id. PER-PROC-MOD 208 mayalso check for matching CRE-class (ID-CLASS) in theGLOB-SEL-PER-REC-TABLE and may decide to include it in the selectiveperception information to be sent as part of the perception distributioninformation. Similarly, for collective perception information,PER-PROC-MOD 208 checks if there is any update in the GLOB-COL-PER-RECcorresponding to the CRE in the GLOB-COL-PER-REC-TABLE, and if there isany update, PER-PROC-MOD 208 may include it in the collective perceptioninformation to be sent as part of the perception distributioninformation. PER-PROC-MOD 208 then composes the selective perceptioninformation and collective perception information thus extracted, andsends it to PER-SCHED-RSP-MOD 210. PER-SCHED-RSP-MOD 210 then schedulesthe perception distribution information to be sent in the perceptionresponse (PER-RSP) using the same communication channel over which theperception request was received.

In another embodiment, the perception distribution information may bedetermined in response to a predefined trigger event/exception. Thiscase arises when one or more exceptions have been reported to PMM 202.PER-PROC-MOD 208 determines the communication network (for example,IoTNs) to which the selective perception information has to be sent byaccessing the GCE-REC-TABLE. Additionally, PER-PROC-MOD 208 fetchesdetails of the relevant communication networks which have communicatedwith the particular CRE during a predefined period, for example, duringthe last 15 days. Based on the type of exception, PER-PROC-MOD 208 mayalso fetch details of the relevant communication networks (in order tosend the selective perception information) which have communicated withthose CREs whose CRE-type is the same as the one which caused theexception.

PER-PROC-MOD 208 may then form a distribution list that includes one ormore communication entities to whom the selective perception informationshould be sent. PER-PROC-MOD 208 then sends the distribution list toPER-SCHED-RSP-MOD 210. PER-SCHED-RSP-MOD 210 checks if the criticalitylevel of the exception (EXC-CRT-LVL) is greater than a pre-definedthreshold (EXC-CRT-LVL-THRESH). If the EXC-CRT-LVL is greater thanEXC-CRT-LVL-THRESH, then PER-SCHED-RSP-MOD 210 schedules thetransmission of the perception information through fast channels and/orimmediate transmission over available channels. If the EXC-CRT-LVL isnot greater than EXC-CRT-LVL-THRESH, then PER-SCHED-RSP-MOD 210 maydecide to send the information over normal (non-priority) channels ormay defer the transmission until the next time-interval basedtransmission of perception info. PER-SCHED-RSP-MOD 210 may also decideto send certain information over priority/fast channels even when theEXC-CRT-LVL is not greater than EXC-CRT-LVL-THRESH, if based on pastlearning (by comparing exception trends in current session with trendsin past sessions involving the CRE), further exceptions or undesirableevents are predicted to occur in a short timeframe (e.g., within thenext 2 minutes).

In yet another embodiment, in response to expiry of a time period,PER-PROC-MOD 208 performs the following steps periodically, for example,once every 30 minutes. For each of the CREs for which an entry ispresent in the GLOBAL-SEL-PER-REC-TABLE, PER-PROC-MOD 208 prepares orupdates collective perception information and updates theGLOB-COL-PER-TABLE. Referring back to step 306, in this case instead ofthe perception data input received, the one or more entries in theGLOBAL-SEL-PER-REC-TABLE may be used as an input for further processing.PER-PROC-MOD 208 fetches all relevant entries that have been updated inthe GLOB-COL-PER-TABLE, for example, by checking the timestamp of lastupdate of entries. This may include the entries updated inGLOBAL-COL-PER-TABLE in above step, as well as entries updated inGLOBAL-COL-PER-TABLE on reception of perception data since the lastperiodic cycle. Further, PER-PROC-MOD 208 forms the distribution list(for example, list of IoTNs) to whom the collective perceptioninformation has to be sent. For example, PER-PROC-MOD 208 may check theIoTNs which have communicated during the last 15 days with those CREswhose entries have been fetched before. PER-PROC-MOD 208 also preparesthe contents of the perception distribution information to be sent toeach of communication entities identified above using the entriesfetched in the steps discussed above.

Based on observation of amount of data sent, for example, once every 30minutes during the last ‘n’ cycles, PER-SCHED-RSP-MOD 210 may learn andadapt the periodicity of time-bound delivery. In an exemplaryembodiment, PER-SCHED-RSP-MOD 210 may use the equation 1 given below tolearn and adapt:NEW-PERIODICITY=CURRENT-PERIODICITY*(STD-DATA-SIZE/AVG-DATA-SIZE)*PERD-SCF  (1)

where,

-   -   NEW-PERIODICITY=Newly computed periodicity    -   CURRENT-PERIODICITY=Existing periodicity    -   STD-DATA-SIZE=Amount of data normally expected to be delivered,        which is a pre-provisioned value. It may be expressed as number        of perception records, or in bytes    -   AVG-DATA-SIZE=Average of amount of data sent in last ‘n’ cycles,        and is computed in the same measurement unit as STD-DATA-SIZE    -   PERD-SCF=Scaling factor.

Thereafter, at step 310, the network device transmits the perceptiondistribution information to the at least one communication entity. In anembodiment, PER-PROC-MOD 208 may pass the prepared contents along withthe distribution list to PER-SCHED-RSP-MOD 210. PER-SCHED-RSP-MOD 210then schedules the transmission of the perception info to allcommunication entities (for example, IoTNs) in the distribution list. Inanother embodiment, PER-COMM-MOD 212 may transmit the perceptiondistribution information to the list of communication networks (forexample, IoTNs) provided by PER-SCHED-RSP-MOD 210 according to thetransmission schedule and channel info provided by PER-SCHED-RSP-MOD210. PER-COMM-MOD 212 may transmit the perception distributioninformation to the relevant communication networks, for example, to therelevant IoTNs by sending it to the ICG associated with the IoTNs. Atstep 312, the network device may adapt the perception distributioninformation and a plurality of network parameters based on learning fromhistorical data.

Referring now to FIG. 4, a flowchart of a method for provisioningcollective perception in a communication network is illustrated, inaccordance with another embodiment. At step 402 the network device mayreceive a request for perception data from one of a plurality ofcommunication entities.

The request may be sent on initiation of a communication session.Alternatively, the request may be sent in response to a change in statusof the communication session. In an embodiment, PER-COMM-MOD 212 in PMM202 may receive a request for perception input (i.e., PERC-REQST). Therequest may be received at the start of a communication session (whichmay be an IoT session). The request may be received during acommunication session due to a change in one or more of, but not limitedto context or purpose (i.e., change in status) of the communicationsession. PER-COMM-MOD 212 passes the received request toPER-SCHED-RSP-MOD 210 in PMM 202.

Thereafter, at step 404 the network device may process the request forthe perception data to extract information from the request. In anembodiment, PER-SCHED-RSP-MOD 210 extracts the information from thereceived PERC-REQST and stores the details, which may include, but arenot limited to communication channel used, encryption info, priority,criticality, etc. PER-SCHED-RSP-MOD 210 then passes the PERC-REQST toPER-PROC-MOD 208 in order to provide the relevant perception inputs thatare to be sent in response to the PERC-REQST. Thereafter steps 406 and408 are performed, which are analogous to steps 308 and 310. These stepshave already been explained in detail in conjunction with FIG. 3

Referring now to FIG. 5, a flowchart of a method for assimilating theperception data in a GCE-REC-TABLE in response to receiving theperception data from a plurality of communication entities isillustrated, in accordance with an embodiment. Referring back to step304, in order to assimilate the perception data in the GCE-REC-TABLE,the network device, at step 502, ascertains the one or more perceptiondata categories relevant for the perception data received from theplurality of communication entities. The step 502 further include steps504, 506, and 508. It will be apparent to a person skilled in the artthat steps 504, 506, and 508 may be mutually exclusive and are notexecuted in a sequence.

At step 504, the network device may create a new data entry in theGCE-REC-TABLE for one or more of the plurality of communication entitiesfor a communication session. At step 506, the network device may addrelevant perception data associated with a communication entity from theplurality of communication entities, to an existing data entry for thecommunication entity in the GCE-REC-TABLE for a communication session.In an embodiment, EA-MOD 204 may create a GCE-REC entry in theGCE-REC-TABLE, if an entry does not exist for that CRE for that specificIoT session, else EA-MOD 204 updates the relevant entry in theGCE-REC-TABLE. By way of an example, if an exception feed was received,and an entry already exists in the GCE-REC-TABLE for that CRE for thatspecific IoT session, EA-MOD 204 adds the exception context info to theexisting entry.

At step 508, the network device may delete an obsolete data entryassociated with a communication entity from the plurality ofcommunication entities from the GCE-REC-TABLE. In an embodiment, EA-MOD204 also checks if any outdated entries must be removed, and removessuch outdated entries. For example, entries which are older than acertain threshold duration (for example, older than six months), orentries which have never been used beyond a certain duration (forexample, not used during last three months), may be removed from theGCE-REC-TABLE.

Referring now to FIG. 6, a flowchart of a method for processingperception data inputs associated with one or more perception datacategories to create composite perception information is illustrated, inaccordance with an embodiment. Referring back to step 306, the networkdevice processes the perception data associated with each of the one ormore perception data categories to create composite perceptioninformation for each of the one or more perception data categories basedon relevant entries in the GCE-REC-TABLE.

The composite perception information includes selective perceptioninformation and collective perception information. The selectiveperception information for a communication entity includes one or moreof, but is not limited to ID, group ID, class, security level, privacylevel, aggregated fulfillment record, aggregated security compliancerecord, aggregated privacy compliance record, aggregated reliabilityrecord, or overall perception score. The collective perceptioninformation for a communication entity includes one or more of, but isnot limited to ID, group ID, class, exception criticality level,recommended security level, recommended privacy compliance level,recommended fulfillment level, recommended compliance level, recommendedprivacy compliance level, recommended reliability level, or overallrecommendation.

The step 306 includes steps 602, 604, and 606. Though, steps 602 and 604are in sequence, the step 606 is mutually exclusive of the steps 602 and604. At step 602, the network device may update theGLOB-SEL-PER-REC-TABLE with one or more global selective perceptionrecords based on the relevant entries in the GCE-REC-TABLE associatedwith the exception-perception data category. The GLOB-SEL-PER-REC-TABLEincludes selective perception information associated with each of theplurality of communication entities. At step 604, the network device mayrevise criticality level associated with the selective perceptioninformation based on information in the GLOB-SEL-PER-REC-TABLE, when oneor more exception thresholds are crossed.

In an embodiment, PER-PROC-MOD 208 processes the information in theexception feed (EXC-FEED) to create or update the selective perceptioninformation for the CRE using steps given below using the information inthe relevant entries (if present) in the GCE-REC-TABLE associated withthe exception perception data category.

First, criticality level is determined. To this end, the criticalitylevel (EXC-CRT-LVL) of the exception based on exception type andexception details, using the EXC-CRT-MAPPING-TABLE is determined. Usingexception type, exception details, number of occurrences of the sameexception (type as well as the specific exception) during the session(or) within a pre-defined time window, a check is performed to determineif any exception thresholds (EXC-THRES) have been crossed. If one ormore EXC-THRES have been crossed, the criticality level of the exceptionis increased.

Second, recommended privacy or security level and recommended privacy orsecurity compliance level is determined. When the exception is privacyor security related, then based on exception details and past exceptionsencountered during the session, the recommended privacy level(REC-PRIV-LVL-CRE) and the recommended security level (REC-SEC-LVL-CRE)using the REC-PRIV-LVL-TABLE and the REC-SEC-LVL-TABLE respectively aredetermined. Based on learning from past sessions involving the CRE (byexamining past exception trends and privacy-security levels), and thetrend of exceptions (type and number) until now in the present session,the REC-PRIV-LVL-CRE and REC-SEC-LVL-CRE are adapted. Additionally,based on the learning, PER-PROC-MOD 208 may also adapt the entries inREC-PRIV-LVL-TABLE and REC-SEC-LVL-TABLE for future use.

Further, based on exception details and past exceptions encounteredduring the session, the recommended privacy compliance level(REC-PRIV-COMPL-LVL-CRE) and the recommended security compliance level(REC-SEC-COMPL-LVL-CRE) using the REC-PRIV-COMPL-LVL-TABLE and theREC-SEC-COMPL-LVL-TABLE respectively are determined. Based on learningfrom past sessions involving the CRE (by examining past exception trendsand privacy-security levels), and the trend of exceptions (type andnumber) until now in the present session, the REC-PRIV-COMPL-LVL-CRE andREC-SEC-COMPL-LVL-CRE are determined. Based on the learning,PER-PROC-MOD. 208 may also adapt the entries in REC-PRIV-COMPL-LVL-TABLEand REC-SEC-COMPL-LVL-TABLE for future use.

Third, recommended need fulfillment level is determined. Using exceptiontype, number of occurrences of the exception type in the session tillthat instant, the recommended need fulfillment level(REC-NEED-FULFILL-LVL-CRE) using relevant information in theREC-NEED-FULFILL-LVL-TABLE is determined. In an exemplary embodiment,the following steps may be performed:

Based on exception type, the relevant entry(REC-NEED-FULFILL-LVL-TABLE-ENTRY) is fetched fromREC-NEED-FULFILL-LVL-TABLE. Based on the number of occurrences of theexception type, the relevant NEED-FULFILL-FACTOR entry is fetched fromNEED-FULFILL-FACTOR-TABLE.RAW-REC-NEED-FULFILL-LVL-CRE=(REC-NEED-FULFILL-LVL-ENTRY*NEED-FULFILL-FACTOR)is determined, REC-NEED-FULFILL-LVL-CRE=RAW-REC-NEED-FULFILL-LVL-CRE(AGGREG-NEED-FULFILL-REC-CRE*NEED-SCF) is also determined, whereAGGREG-NEED-FULFILL-REC-CRE is fetched from the GLOB-COL-PER-REC-TABLE(if present, else value ‘0’ is taken), and NEED-SCF is a configured(scaling) factor that determines the influence of past need fulfillmentrecord of the CRE on the recommended need fulfillment level. In thiscase, the past need fulfillment record of the CRE is simply added (aftermultiplying by the NEED-SCF which is a scaling factor) toRAW-REC-NEED-FULFILL-LVL-CRE to determine REC-NEED-FULFILL-LVL-CRE.REC-NEED-FULFILL-LVL-CRE may also be computed using more complex means,for example, using a polynomial involving RAW-REC-NEED-FULFILL-LVL-CREand AGGREG-NEED-FULFILL-REC-CRE. The REC-NEED-FULFILL-LVL-CRE may alsobe adapted based on the learning from past sessions. This is done byanalyzing the trend of number of types of exceptions encountered in thecurrent session and comparing it with trends in historical datainvolving the CRE (which is available in GCE-REC-TABLE), fetching therelevant EXP-NEED-FULFILL-REC-CRE values, and using them to adapt theREC-NEED-FULFILL-LVL-CRE, for example, using an additive factor such asa weighted average, or using complex polynomial factors.

Fourth, recommended reliability level is determined. The REC-REL-LVL-CREof the CRE is determined based on the current exception, number andtypes of past exceptions during the session. In an exemplary embodiment,the following method may be used. For each exception, based on the typeand criticality level (EXC-CRT-LVL) that occurred in the session,determine: REL-LVL=REL-VALUE*REL-FACTOR, where, REL-VALUE is fetchedfrom the REL-VALUE-TABLE based on the exception type and criticalitylevel and REL-FACTOR is fetched from the REL-FACTOR-TABLE.TOTAL-REL-LVL=Weighted average of individual REL-LVL determined above,wherein higher weights could be assigned to most recent exceptionsand/or exceptions with higher criticality, etc. Then REC-REL-LVL-CRE isdetermined as REC-REL-LVL-CRE=TOTAL-REL-LEVELAGGREG-REL-REC-CRE*REL-SCF, where, AGGREG-REL-REC-CRE is fetched fromthe GLOB-COL-PER-REC-TABLE (if present, else value ‘0’ is taken), andREL-SCF is a configured factor that determines the influences of thepast reliability record of the CRE on the recommended reliability level.In this case, the past reliability record of the CRE is simply added(after multiplying by the REL-SCF which is a scaling factor) toTOTAL-REL-LEVEL to determine REC-REL-LVL-CRE. REC-REL-LVL-CRE may alsobe computed using more complex means, for example, using a polynomialinvolving TOTAL-REL-LEVEL and AGGREG-REL-REC-CRE.

Fifth, overall recommendation for CRE is determined. This could be aweighted average of the recommended security and privacy levels of theCRE, recommended need fulfillment level, recommended security andprivacy levels, recommended security and privacy compliance levels andrecommended reliability level with greater weightage assigned to thefactors associated with the exception currently received, and adjustedbased on historical data when similar exceptions were encountered forthe same class of CREs. It could also be determined based on morecomplex methods, for example, considering also the criticality ofexceptions received, weightage based on the communication context.PER-PROC-MOD 208 then creates or updates the relevant entry in theGLOB-SEL-PER-REC-TABLE.

At step 606, processing the perception data comprises updating theGLOB-COL-PER-REC-TABLE with one or more global collective perceptionrecords based on the relevant entries in the GCE-REC-TABLE associatedwith the regular-perception data category. The GLOB-COL-PER-REC-TABLEincludes collective perception information associated with each of theplurality of communication entities. In an embodiment, PER-PROC-MOD 208processes the information in the PER-FEED to create or update thecollective perception information for the CRE using the informationreceived in the relevant entries in the GCE-REC-TABLE. In an exemplaryembodiment, the following steps may be used. First, trustworthiness ofthe information is determined. The trustworthiness or accuracy factor(of the sender) of the information (SNDR-TRUST-FACTOR) may be determinedsimply as a factor corresponding to the PERC-SCORE of the sender, orusing complex steps including computing the standard deviation (STD-DEV)of the inputs provided by the sender and the inputs provided by othersfor the same CRE, computing the PERC-SCORE of the sender for sessionswith similar type of CREs (PERC-SCORE-SIMIL), and then computingTRUST-FACTOR by adjusting the PERC-SCORE-SIMIL by a factor correspondingto the STD-DEV.

Second usual security or privacy level of CRE are determined. The usualsecurity level of the CRE (USU-SEC-LVL-CRE) may be determined asfollows. New value of USU-SEC-LVL-CRE=TRUST-FACTOR*Weighted average ofEXP-SEC-LVL-CRE fetched from the PER-FEED and ‘n’ entries ofEXP-SEC-LVL-CRE for that CRE fetched from the GCE-REC-TABLE for last ‘n’transactions or sessions ‘n’ is a provisioned parameter). Typically,higher weights will be assigned to more recent entries. Higher weightscould also be assigned to those entries which have a higher weightedscore of security-related exceptions (sum of security-relatedexceptions*criticality). The usual privacy level of the CRE(USU-PRIV-LVL-CRE) may be determined as follows:USU-PRIV-LVL-CRE=TRUST-FACTOR*Weighted average of EXP-PRIV-LVL-CREfetched from the PER-FEED and ‘n’ values of E×P-PRIV-LVL-CRE for thatCRE fetched from the GCE-REC-TABLE for last ‘n’ transactions orsessions. Typically, higher weights will be assigned to more recententries. Higher weights could also be assigned to those entries whichhave a higher weighted score of privacy-related exceptions (where,weighted score of privacy-related exceptions=average (privacy-relatedexceptions*criticality)). Instead of weighted average method, morecomplex methods could also be used which take into consideration factorssuch as location, time of day, privacy level of the remote partyinvolved in the communication session, etc.

Third, aggregated need fulfillment level of CRE is determined. In anexemplary embodiment, the aggregated need fulfillment level may bedetermined as: AGGREG-NEED-FULFILL-REC-CRE=TRUST-FACTOR*Weighted averageof EXP-NEED-FULFILL-REC-CRE received in the PER-FEED and ‘n’ most recentvalues of E×P-NEED-FULFILL-REC-CRE fetched from the GCE-REC-TABLE.Higher weights could be assigned to more recent entries.

Fourth, aggregated security or privacy compliance level of CRE isdetermined. In an exemplary embodiment, the aggregated securitycompliance of the CRE may be determined as: WEIGHTED-SEC-EXCEP=Sum(security exception*criticality), where repeated occurrence of the sameexception/exception type are counted separately to account for themultiple occurrences. SEC-COMPL-LVL-SESSION=SEC-COMPL-LVL correspondingto the WEIGHTED-SEC-EXCEP, obtained from the SEC-COMPL-LVL-TABLE. Newvalue of AGGREG-SEC-COMPL-REC-CRE=Weighted average of(SEC-COMPL-LVL-SESSION and AGGREG-SEC-COMPL-REC-CRE*‘n’), with a higherweightage assigned to SEC-COMPL-LVL-SESSION. Since this method involvesconsidering all historic values of SEC-COMPL-REC-CRE, theSEC-COMPL-LVL-SESSION may be computed for the most recent ‘n’ sessionsfor the CRE and stored as a field in the GLOB-PER-REC, and each time asession is completed, the oldest SEC-COMPL-LVL-SESSION value isdiscarded, and the current SEC-COMPL-LVL-SESSION is included.

The aggregated privacy compliance of the CRE may be determined as:WEIGHTED-PRIV-EXCEP=Sum (privacy exception*criticality), where repeatedoccurrence of the same exception/exception type are counted separatelyto account for the multiple occurrence.PRIV-COMPL-LVL-SESSION=PRIV-COMPL-LVL corresponding to theWEIGHTED-PRIV-EXCEP, obtained from the PRIV-COMPL-LVL-TABLE. New valueof AGGREG-PRIV-COMPL-REC-CRE=Weighted average of (PRIV-COMPL-LVL-SESSIONand AGGREG-PRIV-COMPL-REC-CRE*‘n’), with a higher weightage assigned toPRIV-COMPL-LVL-SESSION. Since this method involves considering allhistoric values of PRIV-COMPL-REC-GRE, the PRIV-COMPL-LVL-SESSION may becomputed for the most recent ‘n’ sessions for the CRE and stored as afield in the GLOB-PER-REC, and each time a session is completed, theoldest PRIV-COMPL-LVL-SESSION value is discarded, and the currentPRIV-COMPL-LVL-SESSION is included.

Fifth, aggregated reliability score of the CRE is determined. In anexemplary embodiment, the aggregated reliability score of the CRE(AGGREG-REL REC-CRE) may be determined as an average of the newlycomputed AGGREG-NEED-FULFILL-REC-CRE, AGGREG-SEC-COMPL-REC-CRE andAGGREG-PRIV-COMPL-REC-CRE. It may also be determined using more complexmethods such as taking a weighted average of these three factors, withthe weights being determined based on the security and privacyexceptions attributable to the CRE, number and criticality of exceptionsrelated to need fulfillment, etc.

Sixth, the overall perception score is determined. In an exemplaryembodiment, the overall perception score may be determined as:OVERALL-EXC-FACTOR=exceptions attributable to the CRE during the session(i.e., reason for the exception is CRE, and not the network,interference, external agents, etc.)*criticality*REL-FACTOR, where,REL-FACTOR is determined from REL-FACTOR-TABLE based on the exceptiontype (for example, security, privacy, need-fulfillment relatedexceptions could correspond a higher factor). New PERC-SCORE=Weightedaverage of current PERC-SCORE and OVERALL-EXC-FACTOR, with a higherweightage assigned to the OVERALL-EXC-FACTOR. PER-PROC-MOD 208 thencreates or updates the GLOB-COL-PER-REC entry in theGLOB-COL-PER-REC-TABLE with the values as computed above.

Seventh, new delivery schedule is determined. In an embodiment,PER-PROC-MOD 208 may also increment the number of perception entries tobe distributed (NBR-ENTR-DIST) in the next time-bound cycle by a valueequal to the number of IoTNs to which the update in theGLOB-COL-PER-REC-TABLE has to be communicated (by checking the IoTNs whocommunicated with the CRE, say, during last 15 days). If NBR-ENTR-DISTis greater than a certain threshold (NBR-ENTR-DIST-THRES), PER-PROC-MOD208 may modify the time at which the next time-bound schedule ofdelivery of perception info is to happen. The following equation may beused:NEW-DELIV-SCHED=CURR-DELIV-SCHED−(NBR-ENTR-DIST-NBR-ENTR-DIST-THRES)*DELIV-SCF),where NEW-DELIV-SCHED=newly determined delivery schedule,CURR-DELIV-SCHED=current delivery schedule, DELIV-SCF=scaling factor foradapting the delivery schedule (provisioned value).

It will be appreciated that, for clarity purposes, the above describedembodiments of the invention with reference to different functionalunits and processors. However, it will be apparent that any suitabledistribution of functionality between different functional units,processors or domains may be used without detracting from the invention.For example, functionality illustrated to be performed by separateprocessors or controllers may be performed by the same processor orcontroller. Hence, references to specific functional units are only tobe seen as references to suitable means for providing the describedfunctionality, rather than indicative of a strict logical or physicalstructure or organization.

Various embodiments describe method and device for provisioningcollective perception in communication networks. The method facilitatesglobal collective perception refinement and maintenance. The methodenables assimilation of collected experience and exceptions fromdifferent member communication network into global perception, based ontype of communicating entities and nature of communication andcommunication environment, along with associated exceptions(security/privacy or any other) to form the collective perception.Additionally, the method enables effective distribution of globalperception (usual, need-based, exceptions: push-pull).

The specification has described method and device for provisioningcollective perception in communication networks. The illustrated stepsare set out to explain the exemplary embodiments shown, and it should beanticipated that ongoing technological development will change themanner in which particular functions are performed. These examples arepresented herein for purposes of illustration, and not limitation.Further, the boundaries of the functional building blocks have beenarbitrarily defined herein for the convenience of the description.Alternative boundaries can be defined so long as the specified functionsand relationships thereof are appropriately performed. Alternatives(including equivalents, extensions, variations, deviations, etc., ofthose described herein) will be apparent to persons skilled in therelevant art(s) based on the teachings contained herein. Suchalternatives fall within the scope and spirit of the disclosedembodiments.

Furthermore, one or more computer-readable storage media may be utilizedin implementing embodiments consistent with the present disclosure. Acomputer-readable storage medium refers to any type of physical memoryon which information or data readable by a processor may be stored.Thus, a computer-readable storage medium may store instructions forexecution by one or more processors, including instructions for causingthe processor(s) to perform steps or stages consistent with theembodiments described herein. The term “computer-readable medium” shouldbe understood to include tangible items and exclude carrier waves andtransient signals, i.e., be non-transitory. Examples include randomaccess memory (RAM), read-only memory (ROM), volatile memory, cloud,virtual storage, nonvolatile memory, hard drives, CD ROMs, DVDs, flashdrives, disks, and any other known physical storage media.

The methods described may also be practiced in a distributed computingenvironment where functions are performed by remote processing devicesthat are linked through a communication network. In a distributedcomputing environment, computer executable instructions may be locatedin both local and remote computer storage media, including memorystorage devices.

It is intended that the disclosure and examples be considered asexemplary only, with a true scope and spirit of disclosed embodimentsbeing indicated by the following claims.

What is claimed is:
 1. A method of provisioning collective perception ina communication network, the method comprising: receiving, by a networkdevice, a perception data from a plurality of communication entities inthe communication network upon satisfaction of at least one ofpredefined criteria; assimilating, by the network device, the perceptiondata in a global collective experience record table in response toreceiving the perception data from the plurality of communicationentities, based on at least one perception data category associated withthe predefined criteria; processing, by the network device, theperception data associated with each of the at least one perception datacategory to create composite perception information for each of the atleast one perception data category based on entries in the globalcollective experience record table, wherein the perception data isprocessed based on an associated perception data category; determining,by the network device, perception distribution information to be sharedwith at least one communication entity from the plurality ofcommunication entities, based on the composite perception informationcreated for each of the at least one perception data category, whereinthe perception distribution information is determined based on a requestreceived for the perception data, a predefined trigger event and expiryof a predefined time period; and transmitting, by the network device,the perception distribution information to the at least onecommunication entity, in response to determining, wherein assimilatingcomprises ascertaining, by the network device, the at least oneperception data category relevant for the perception data received fromthe plurality of communication entities, and ascertaining comprises atleast one of: creating, in the global collective experience recordtable, a new data entry for at least one of the plurality ofcommunication entities for a communication session; adding relevantperception data associated with a communication entity from theplurality of communication entities, to an existing data entry for thecommunication entity in the global collective experience record tablefor a communication session; and deleting an obsolete data entryassociated with a communication entity from the plurality ofcommunication entities from the global collective experience recordtable.
 2. The method of claim 1, further comprising: receiving, by thenetwork device, the request for the perception data from one of theplurality of communication entities, wherein the request is sent oninitiation of a communication session or in response to a change instatus of the communication session; and processing, by the networkdevice, the request for the perception data to extract information fromthe request.
 3. The method of claim 2, wherein the change in statuscomprises at least one of a change of context, a change in need and achange in purpose associated with the communication session.
 4. Themethod of claim 1, wherein the predefined criteria comprise at least oneof: occurrence of an exception during a communication session in thecommunication network; partial completion of the communication session;and completion of the communication session.
 5. The method of claim 1,wherein the at least one perception data category comprises anexception-perception data category and a regular-perception datacategory.
 6. The method of claim 5, wherein processing the perceptiondata comprises: updating global selective perception record table withone or more global selective perception records based on the informationassociated with the exception-perception data category, wherein each ofthe one or more global selective perception records comprise selectiveperception information associated with each of the plurality ofcommunication entities, and wherein for a communication entity, theselective perception information comprises at least one of Identifier(ID), group ID, class, security level, privacy level, aggregatedfulfillment record, aggregated security compliance record, aggregatedprivacy compliance record, aggregated reliability record, or overallperception score; and revising criticality level associated with theselective perception information based on the global selectiveperception table, when at least one exception threshold is crossed. 7.The method of claim 5, wherein processing the perception data comprisesupdating a global collective perception record table with one or moreglobal collective perception records based on the information associatedwith the regular-perception data category, wherein each of the one ormore global collective perception records comprises collectiveperception information associated with each of the plurality ofcommunication entities, wherein for a communication entity, thecollective perception information comprises at least one of: Identifier(ID), group ID, class, exception criticality level, recommended securitylevel, recommended privacy compliance level, recommended fulfillmentlevel, recommended compliance level, recommended privacy compliancelevel, recommended reliability level, or overall recommendation.
 8. Themethod of claim 1, wherein the perception data is associated with eachof the at least one perception data category processed periodicallyafter predefined time period or in response to a predefined triggerevent.
 9. The method of claim 8, wherein the plurality of communicationentities comprises at least one of an IoT network, an IoT device, an IoTGateway (GW), or an Inter Connect GW (ICGW).
 10. The method of claim 1,wherein the communication network is an Internet Of Things Network(IoTN).
 11. The method of claim 1, further comprising adapting theperception distribution information and a plurality of networkparameters based on learning from historical data.
 12. A network devicefor provisioning collective perception in a communication network, thenetwork device comprising: a processor; and a memory storing processorinstructions that, when executed by the processor, cause the processorto: receive a perception data from a plurality of communication entitiesin the communication network upon satisfaction of at least one ofpredefined criteria; assimilate the perception data in a globalcollective experience record table in response to receiving theperception data from the plurality of communication entities, based onat least one perception data category associated with the predefinedcriteria; process the perception data associated with each of the atleast one perception data category to create composite perceptioninformation for each of the at least one perception data category basedon entries in the global collective experience record table, wherein theperception data is processed based on an associated perception datacategory; determine perception distribution information to be sharedwith at least one communication entity from the plurality ofcommunication entities, based on the composite perception informationcreated for each of the at least one perception data category, whereinthe perception distribution information is determined based on a requestreceived for the perception data, a predefined trigger event and expiryof a predefined time period; and transmit the perception distributioninformation to the at least one communication entity, in response todetermining, wherein to assimilate the processor instructions furthercause the processor to ascertain the at least one perception datacategory relevant for the perception data received from the plurality ofcommunication entities, and to ascertain the processor instructionsfurther cause the processor to perform at least one of: create, in theglobal collective experience record table, a new data entry for at leastone of the plurality of communication entities for a communicationsession; add relevant perception data associated with a communicationentity from the plurality of communication entities, to an existing dataentry for the communication entity in the global collective experiencerecord table for a communication session; and delete an obsolete dataentry associated with a communication entity from the plurality ofcommunication entities from the global collective experience recordtable.
 13. The network device of claim 12, wherein the processorinstructions further cause the processor to: receive the request for theperception data from one of the plurality of communication entities,wherein the request is sent on initiation of a communication session orin response to a change in status of the communication session; andprocess the request for the perception data to extract information fromthe request.
 14. The network device of claim 12, wherein the predefinedcriteria comprise at least one of: occurrence of an exception during acommunication session in the communication network; partial completionof the communication session; and completion of the communicationsession.
 15. The network device of claim 12, wherein the at least oneperception data category comprises an exception-perception data categoryand a regular-perception data category.
 16. The network device of claim15, wherein to process the perception data, the processor instructionsfurther cause the processor to: update a global selective perceptionrecord table with one or more global selective perception records basedon the information associated with the exception-perception datacategory, wherein each of the one or more global selective perceptionrecords comprise selective perception information within the compositeperception information associated with each of the plurality ofcommunication entities, and wherein for a communication entity, theselective perception information comprises at least one of Identifier(ID), group ID, class, security level, privacy level, aggregatedfulfillment record, aggregated security compliance record, aggregatedprivacy compliance record, aggregated reliability record, or overallperception score; and revise criticality level associated with theselective perception information based on the global selectiveperception table, when at least one exception threshold is crossed. 17.The network device of claim 15, wherein to process the perception data,the processor instructions further cause the processor to update aglobal collective perception record table with one or more globalcollective perception records based on the information associated withthe regular-perception data category, wherein each of the one or moreglobal collective perception records comprises collective perceptioninformation associated with each of the plurality of communicationentities, wherein for a communication entity, the collective perceptioninformation comprises at least one of: Identifier (ID), group ID, class,exception criticality level, recommended security level, recommendedprivacy compliance level, recommended fulfillment level, recommendedcompliance level, recommended privacy compliance level, recommendedreliability level, or overall recommendation.
 18. The network device ofclaim 12, wherein the processor instructions further cause the processorto adapt the perception distribution information and a plurality ofnetwork parameters based on learning from historical data.